Search Results for "no-code-app-builders"
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Showing 46 open source projects for "no-code-app-builders"
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$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Device Activity Tracker
A phone number can reveal whether a device is active
Device Activity Tracker is a platform created to monitor and log the activity of digital devices across networks, giving users visibility into usage patterns, connection events, app launches, and interaction timelines that can be applied for security monitoring, parental oversight, productivity tracking, or device lifecycle analytics. It integrates with devices via sensors or APIs, continually capturing activity metrics and reporting them to a centralized dashboard that visualizes patterns over time, highlights anomalies, and correlates events across systems or users. ... -
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nanoGPT
The simplest, fastest repository for training/finetuning models
NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare or custom corpora. It emphasizes readability and clarity: the training loop is cleanly written, and the code avoids heavy abstractions, letting students follow the architecture step by step. ... -
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AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
...Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run them in a sandbox environment, and analyze the results with statistical methods. The platform also uses multi-agent debate and automated peer review processes to refine research findings and improve paper quality. By combining literature discovery, experimentation, and writing automation, AutoResearchClaw aims to turn research ideas into conference-ready papers with minimal human intervention. -
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ThingPulse ESP8266 Weather Station
ESP8266 Weather Station library supporting OpenWeatherMap
...The simple class uses the header date and time to set the clock. NTP-based time class written by Fabrice Weinberg. We fixed many bugs and improved performance and changed the API a little bit. Either compare your code to the updated WeatherStationDemo or read through the upgrade guide. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Open Science
Open Science is an open-source, local-first, model-agnostic research
...Users can inspect tool activity, approve sensitive actions, branch earlier conversations, and compare alternative research paths without losing prior work. Immutable artifact versions and detailed provenance connect results to code, inputs, execution history, environment evidence, conversation context, and review findings. -
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Qualify
Claude code to help you do lead research and qualification
...Built with simplicity and extensibility in mind, the project includes REST APIs, database models, and a user interface that can be extended or embedded into existing internal systems. Because it prioritizes lean data structures and predictable code paths, developers can customize pipelines, fields, and behaviors to align with their unique business logic. -
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Growth Lab
An end-to-end growth tool that understands the product
Growth Lab is an open-source agentic growth workspace that connects product understanding, market research, execution, measurement, and iteration. It uses Codex or Claude Code as the runtime and treats natural-language conversations as the control surface. Collectors gather product, market, content, and channel evidence, while executor skills help create, publish, review, and coordinate growth work. Each growth model follows an observe-act-review loop and keeps persistent memory of evidence, actions, results, and recommended next steps. ... -
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OpenScience
The open-source AI workbench for scientific research
OpenScience is an open-source AI workbench for scientific research. It lets users give an agent a research goal, then have it read literature, form hypotheses, write and run code, run experiments, analyze results, and write up findings. The workspace runs in the browser and includes a file tree, editor, terminal, session history, and scientific rendering for molecules, structures, genomes, and plots. It supports frontier, open-weight, and local models through bring-your-own-key provider configuration. The project includes research agents, domain specialists, critique agents, literature-review agents, and more than 290 scientific skills. ... -
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AI Researcher
An autonomous AI researcher
...It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they communicate through a task-management interface that ensures progress tracking and iterative refinement. The system emphasizes modularity, so teams can swap in new reasoning modules, data retrieval strategies, or domain knowledge bases depending on the research topic. ... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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ClooWrapperVBA
COM-wrapper of Cloo to execute OpenCL code from Excel.
The wrapper allows to execute OpenCL code on CPU and GPU devices from VBA. Sources are available under https://github.com/Excel-lent/ClooWrapperVBA -
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KingJamesPureBibleSearch
GUI Application to Search and Count the Pure King James Bible
...For more info and downloads, see http://www.purebiblesearch.com/ For details on the King James Code, see http://visitbethelchurch.com/ -
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Brain Tokyo Workshop
Experiments and code from Google Brain’s Tokyo research workshop
The Brain Tokyo Workshop repository hosts a collection of research materials and experimental code developed by the Google Brain team based in Tokyo. It showcases a variety of cutting-edge projects in artificial intelligence, particularly in the areas of neuroevolution, reinforcement learning, and model interpretability. Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. ... -
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Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. Catalyst is compatible with Python 3.6+. ... -
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Key Store
Scriptural Keys Restoration - decoded universally symbolic language
The Key Store is a directory where users can find the symbolic meaning to a word as defined in Holy Scripture. These are often referred to as the keys of the Kingdom of Heaven. Much like a secret code, the directory exposes a universal dialect, all but nearly lost throughout the Dark Ages of time. Yet, fragments of this language remained until today such as, Father = Time and Mother = Nature. The database is expandable to grow as more entries and the sources are uncovered. -
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VXUG-Papers
Research code & papers from members of vx-underground
VXUG-Papers is an archive of security research papers, proof-of-concept code, and technical experiments contributed by members of the vx-underground community. Its contents focus heavily on malware research, operating system internals, persistence, process behavior, propagation, and offensive-security techniques. The repository mixes written papers with source files, demonstrations, and project folders. Topics span Windows, Linux, Android, virtualization, credential research, loaders, and other low-level subjects. ... -
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covid19model
Code for modelling estimated deaths and cases for COVID19
...Peer-reviewed version is to be out soon. All other code is still the same for previous releases. The code should be run in full mode to obtain credible results. Not running a full run to estimate anything is not recommended and discouraged. Only a full run should be used to get results. -
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Lucid
A collection of infrastructure and tools for research
Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud. ... -
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hubs-research-acm-chi-2021
Supplemental code and dataset for the ACM CHI 2021 paper
Supplemental code and dataset for the ACM CHI 2021 paper on "Proxemics and Social Interactions in an Instrumented Virtual Reality Workshop". In this research paper we instrumented Mozilla Hubs Cloud to record where participants where during the event. From there, we measured proxemic and plotted the activity along with some semi-structured interviews. -
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
...All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run export KENLM_ROOT_DIR=... so that wav2letter++ can find it. This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. Each dataset (test/valid/train) needs to be in a separate file with one sample per line. ... -
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...Installation Videos! Part 1: http://youtu.be/rnv2VLcG-eI Part 2: http://youtu.be/eFudbMWHNlQ Special thanks to Wells Oliver for the code for downloading Retrosheet files. And the Chadwick project for its Retrosheet tools. https://sourceforge.net/projects/chadwick/?source=recommended
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Data Science at the Command Line
Data science at the command line
Command Line by Jeroen Janssens, published by O’Reilly Media in October 2021. Obtain, scrub, explore, and model data with Unix Power Tools. This repository contains the full text, data, and scripts used in the second edition of the book Data Science at the Command Line by Jeroen Janssens. This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful... -
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Pydicom by examples
Basic and intermediate examples of DICOM library with Jupyter
Basic and intermediate examples to read, modify and write DICOM files with Python code using Jupyter - To install Jupyter - https://jupyter.org/install ====== All examples are based on Pydicom. An open source library - https://pydicom.github.io/ -
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FB Chart Designer
Create multi-degree polynominals charts. Designed in FbEdit & WinAPI.
...This is the one of the fastest way to create window application with visual design methods, and implement into it an ellegant and flexible chart, that can be choosen from four different diagram kinds (if you edit code and use it in your projects). The source code chart library by Lothar Schirm is based on the consolidated solutions from FireFly Designer by Paul Squires. FB Chart Designer shows the complete example of connection those mentioned solutions to achieve thiny file and less code project. It makes more simply to analyze code and provides faster implementation of rebuilted chart library. ... -
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Pascal NUCLEUS (GUI/VM)
Portable Pascal GUI Library for Atari ST/TT/MSDOS
...The code current compiles with Highspeed Pascal (Atari ST) or FreePascal. I hope to have it compiling for the Amiga (also using Highspeed Pascal), and supporting a built in p-code compiler/interpreter for cross platform development. -
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Deep Learning for Medical Applications
Deep Learning Papers on Medical Image Analysis
Deep-Learning-for-Medical-Applications is a repository that compiles deep learning methods, code implementations, and examples applied to medical imaging and healthcare data. The project addresses domain-specific challenges like segmentation, classification, detection, and multimodal data (e.g. MRI, CT, X-ray) using state-of-the-art architectures (e.g. U-Net, ResNet, GAN variants) tailored to medical constraints (small datasets, annotation costs, class imbalance).